mlr_learners_dens.pen: Density Penalized Learner

In mlr3learners/mlr3learners.pendensity: Learners from the {pendensity} package for 'mlr3'

Description

A mlr3proba::LearnerDens implementing penalized estimation from package pendensity. Calls pendensity::pendensity().

Dictionary

This Learner can be instantiated via the dictionary mlr_learners or with the associated sugar function lrn():

mlr_learners$get("dens.pen")
lrn("dens.pen")

Super classes

mlr3::Learner -> mlr3proba::LearnerDens -> LearnerDensPenalized

Methods

Public methods

• LearnerDensPenalized$new()

• LearnerDensPenalized$clone()

Inherited methods

• mlr3::Learner$format()

• mlr3::Learner$help()

• mlr3::Learner$predict()

• mlr3::Learner$predict_newdata()

• mlr3::Learner$print()

• mlr3::Learner$reset()

• mlr3::Learner$train()

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Method new()

Creates a new instance of this R6 class.

Usage

LearnerDensPenalized$new()

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Method clone()

The objects of this class are cloneable with this method.

Usage

LearnerDensPenalized$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

References

Density Estimation with a Penalized Mixture Approach, Schellhase C. and Kauermann G. (2012), Computational Statistics 27 (4), p. 757-777.

See Also

Dictionary of Learners: mlr3::mlr_learners

Examples

if (requireNamespace("pendensity")) {
  learner = mlr3::lrn("dens.pen")
  print(learner)

  # available parameters:
  learner$param_set$ids()
}

mlr3learners/mlr3learners.pendensity documentation built on July 31, 2020, 9:31 a.m.